Engineering Manager, Data Platform - MNTN

Polluxa, Inc.; United States; On-site; USD 180,000 - 230,000; Full time

Job summary

MNTN is seeking an Engineering Manager for the Data Platform team. This hands-on leadership role will guide the architecture, roadmap, and execution while staying close to code.

You’ll mentor engineers and partner with data science, analytics, product, and engineering teams to shape platform features and drive scalable data workflows. The ideal candidate has experience leading data/platform initiatives, ability to set a high technical bar, and a passion for growing a strong engineering team in a

Qualifications

• Experience leading data/platform teams
• Hands-on software engineering leadership
• Strong architectural and coding skills
• Mentoring and growing engineers

Responsibilities

• Lead the Data Platform team in designing, building, and maintaining core infrastructure and tooling for analytics, data science, and data engineering workloads.
• Collaborate with Principal Engineer to define the technical roadmap and architecture.
• Partner with cross-functional teams to understand use cases and shape platform features.
• Ensure high reliability, scalability, and observability of data platforms and governance.
• Establish and enforce best practices for data engineering and platform development.

Job description

At MNTN, we put our people first, full stop. This allows our company culture to be defined by our team members and their shared values, like trust, ambition, quality, radical honesty, and compassionate leadership. It’s why we all really love working for the Hardest Working Software in Television™ (and also why we were named one of Ad Age’s Best Places To Work in 2026.)

We pride ourselves on bringing unrivaled performance and simplicity to Connected TV advertising. Our self-serve technology makes running TV ads as easy as search and social, helping brands drive measurable conversions, revenue, site visits, and more. It’s what led MNTN to being named one of Fast Company's Most Innovative Companies in 2023. You can learn more about us and everything we do by visiting https://mountain.com/ .

We’re committed to innovation that empowers, not replaces. At MNTN, AI is a tool for growth, enhancing efficiency while keeping a people-first approach. Our goal is to streamline workflows and drive new solutions—without compromising the human element that makes our company great.

So if wanting to do more, own more, and make a bigger impact comes naturally to you, then you may be the person we're looking for to join us in our next stage of growth.

The Data Platform team builds the foundational data infrastructure and tooling that empowers data engineers, analysts, and data scientists across MNTN. The team owns the internal data platform as a product: enabling high-quality, self-serve, and scalable data workflows through well-designed systems and strong engineering practices, covering everything from ingestion and transformation to orchestration, observability, and governance.

We're looking for an Engineering Manager to lead the Data Platform team, working closely with a Staff Engineer to define the roadmap, coordinate execution, and ensure the team delivers high-leverage tools and systems for its internal customers. This is a hands-on engineering leadership role. The ideal candidate stays close to the code, contributes to key projects, and sets a strong technical bar while supporting and growing a team of engineers.

What you'll do

• Lead the Data Platform team in designing, building, and maintaining core infrastructure and tooling to support analytics, data science, and data engineering workloads.
• Partner with the Principal Engineer to define the team’s technical roadmap and architecture.
• Collaborate cross-functionally with data science, analytics, product, and engineering teams to understand use cases and shape platform features accordingly.
• Ensure high reliability, scalability, and usability of the data platform—covering areas like data ingestion, transformation, orchestration, observability, and governance.
• Establish and enforce best practices for data engineering and platform development.